AIMC Topic: Algorithms

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Evaluating and mitigating bias in AI-based medical text generation.

Nature computational science
Artificial intelligence (AI) systems, particularly those based on deep learning models, have increasingly achieved expert-level performance in medical applications. However, there is growing concern that such AI systems may reflect and amplify human ...

AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition.

IEEE transactions on cybernetics
The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and representations within and between individuals. However, current works primarily align the distributions of ...

Multicontact Safety-Critical Planning and Adaptive Neural Control of a Soft Exosuit Over Different Terrains.

IEEE transactions on cybernetics
Many previous works on wearable soft exosuits have primarily focused on assisting human motion, while overlooking safety concerns during movement. This article introduces a novel single-motor, altering bi-directional transfer soft exosuit based on im...

HATNet: EEG-Based Hybrid Attention Transfer Learning Network for Train Driver State Detection.

IEEE transactions on cybernetics
Electroencephalography (EEG) is widely utilized for train driver state detection due to its high accuracy and low latency. However, existing methods for driver status detection rarely use the rich physiological information in EEG to improve detection...

LACE-UP: An ensemble machine-learning method for health subtype classification on multidimensional binary data.

Proceedings of the National Academy of Sciences of the United States of America
Disease and behavior subtype identification is of significant interest in biomedical research. However, in many settings, subtype discovery is limited by a lack of robust statistical clustering methods appropriate for binary data. Here, we introduce ...

The predictive role of identifying frailty in assessing the need for palliative care in the elderly: the application of machine learning algorithm.

Journal of health, population, and nutrition
BACKGROUND: Palliative care is a key component of integrated care to improve care quality and reduce hospitalization costs for patients with chronic obstructive pulmonary disease (COPD). This study aims to use machine learning algorithms to create an...

Random forest algorithm for predicting tobacco use and identifying determinants among pregnant women in 26 sub-Saharan African countries: a 2024 analysis.

BMC public health
INTRODUCTION: Tobacco use during pregnancy is a significant public health concern, associated with adverse maternal and neonatal outcomes. Despite its critical importance, comprehensive data on tobacco use among pregnant women in sub-Saharan Africa i...

Incorporation of explainable artificial intelligence in ensemble machine learning-driven pancreatic cancer diagnosis.

Scientific reports
Despite the strides made in medical science, pancreatic cancer continues to be a threat, highlighting the urgent need for creative strategies to address this concern. Recently, a potential approach that has attracted significant attention is using ma...

Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks.

Scientific reports
Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular screenings to prevent its progression to severe stages. Manual diagnosis is labor-intensive and prone to inaccuracies, highlighting the need for automat...

Improved food image recognition by leveraging deep learning and data-driven methods with an application to Central Asian Food Scene.

Scientific reports
The burden of diet-related diseases is high in Central Asia. In recent years, the field of food computing has gained prominence due to advancements in computer vision (CV) and the increasing use of smartphones and social media. These technologies pro...